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   "source": [
    "# End of week 1 exercise\n",
    "\n",
    "## Dynamically pick an LLM provider to let MathXpert answer your math questions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1070317-3ed9-4659-abe3-828943230e03",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from enum import StrEnum\n",
    "from getpass import getpass\n",
    "\n",
    "from dotenv import load_dotenv\n",
    "from openai import OpenAI\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display, clear_output, Markdown, Latex\n",
    "\n",
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f169118a-645e-44e1-9a98-4f561adfbb08",
   "metadata": {},
   "source": [
    "## Free Cloud Providers\n",
    "\n",
    "Grab your free API Keys from these generous sites:\n",
    "\n",
    "- https://openrouter.ai/\n",
    "- https://ollama.com/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a456906-915a-4bfd-bb9d-57e505c5093f",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Provider(StrEnum):\n",
    "    OLLAMA = 'Ollama'\n",
    "    OPENROUTER = 'OpenRouter'\n",
    "\n",
    "models: dict[Provider, str] = {\n",
    "    Provider.OLLAMA: 'gpt-oss:120b-cloud',\n",
    "    Provider.OPENROUTER: 'qwen/qwen3-4b:free'\n",
    "}\n",
    "\n",
    "def get_api_key(env_name: str) -> str:\n",
    "    '''Gets the value from the environment, otherwise ask the user for it if not set'''\n",
    "    key = os.environ.get(env_name)\n",
    "    if not key:\n",
    "        key = getpass(f'Enter {env_name}:').strip()\n",
    "\n",
    "    if key:\n",
    "        print(f'✅ {env_name} provided')\n",
    "    else:\n",
    "        print(f'❌ {env_name} provided')\n",
    "    return key\n",
    "\n",
    "\n",
    "providers: dict[Provider, OpenAI] = {}\n",
    "\n",
    "if api_key := get_api_key('OLLAMA_API_KEY'):\n",
    "    providers[Provider.OLLAMA] = OpenAI(base_url='https://ollama.com/v1', api_key=api_key)\n",
    "\n",
    "if api_key := get_api_key('OPENROUTER_API_KEY'):\n",
    "    providers[Provider.OPENROUTER] = OpenAI(base_url='https://openrouter.ai/api/v1', api_key=api_key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8d7923c-5f28-4c30-8556-342d7c8497c1",
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   "source": [
    "def get_messages(question: str) -> list[dict[str, str]]:\n",
    "    \"\"\"Generate messages for the chat models.\"\"\"\n",
    "\n",
    "    system_prompt = '''\n",
    "    You are MathXpert, an expert Mathematician who makes math fun to learn by relating concepts to real \n",
    "    practical usage to whip up the interest in learners.\n",
    "    \n",
    "    Explain step-by-step thoroughly how to solve a math problem. Respond in **LaTex**'\n",
    "    '''\n",
    "\n",
    "    return [\n",
    "        {'role': 'system', 'content': system_prompt },\n",
    "        {'role': 'user', 'content': question},\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef72c85e",
   "metadata": {},
   "outputs": [],
   "source": [
    "get_messages('Explain how to solve a differentiation problem')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aae1579b-7a02-459d-81c6-0f775d2a1410",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_provider, client = next(iter(providers.items()))\n",
    "\n",
    "def on_provider_change(change):\n",
    "    global selected_provider, client\n",
    "\n",
    "    selected_provider = change['new']\n",
    "    client = providers.get(selected_provider)\n",
    "\n",
    "\n",
    "provider_selector = widgets.Dropdown(\n",
    "    options=list(providers.keys()),\n",
    "    description='Select an LLM provider:',\n",
    "    style={'description_width': 'initial'},\n",
    ")\n",
    "\n",
    "provider_selector.observe(on_provider_change, names='value')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f7c8ea8-4082-4ad0-8751-3301adcf6538",
   "metadata": {},
   "outputs": [],
   "source": [
    "handle = display(None, display_id=True)\n",
    "\n",
    "def ask(client: OpenAI, model: str, question: str):\n",
    "    try:\n",
    "        prompt = get_messages(question=question)\n",
    "        response = client.chat.completions.create(\n",
    "            model=model,\n",
    "            messages=prompt,\n",
    "            stream=True,\n",
    "        )\n",
    "    \n",
    "        output = ''\n",
    "        for chunk in response:\n",
    "            output  += chunk.choices[0].delta.content or ''\n",
    "    \n",
    "            handle.update(Latex(output))\n",
    "    except Exception as e:\n",
    "        clear_output(wait=True) \n",
    "        print(f'🔥 An error occurred: {e}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "09bc9a11-adb4-4a9c-9c77-73b2b5a665cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "display(provider_selector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e01069b2-fd2c-446f-b385-09c1d9624225",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_label = \"Ask your question (Type 'q' to quit): \"\n",
    "question = input(input_label)\n",
    "\n",
    "while question.strip().lower() not in ['quit', 'q']:\n",
    "    clear_output(wait=True)\n",
    "    print(selected_provider, models[selected_provider])\n",
    "    model = models[selected_provider]\n",
    "    ask(client, model, question)\n",
    "\n",
    "    question = input(input_label)"
   ]
  }
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